Malaria infection and its association with socio-demographics, long lasting insecticide nets usage and hematological parameters among adolescent patients in rural Southwestern Nigeria

Background There is increasing evidence suggesting that adolescents are contributing to the populations at risk of malaria. This study determined the prevalence of malaria infection among the adolescents and examined the associated determinants considering socio-demographic, Long Lasting Insecticide Nets (LLINs) usage, and hematological factors in rural Southwestern Nigeria. Methods A hospital-based cross-sectional study was conducted between July 2021 and September 2022 among 180 adolescents who were recruited at a tertiary health facility in rural Southwestern Nigeria. Interviewer administered questionnaire sought information on their socio-demographics and usage of LLINs. Venous blood samples were collected and processed for malaria parasite detection, ABO blood grouping, hemoglobin genotype, and packed cell volume. Data were analyzed using SPSS version 20. A p-value <0.05 was considered statistically significant. Results The prevalence of malaria infection was 71.1% (95% CI: 68.2%-73.8%). Lack of formal education (AOR = 2.094; 95% CI: 1.288–3.403), being a rural residence (AOR = 4.821; 95% CI: 2.805–8.287), not using LLINs (AOR = 1.950; 95% CI: 1.525–2.505), genotype AA (AOR = 3.420; 95% CI: 1.003–11.657), genotype AS (AOR = 3.574; 95%CI: 1.040–12.277), rhesus positive (AOR = 1.815; 95% CI:1.121–2.939), and severe anemia (AOR = 1.533; 95% CI: 1.273–1.846) were significantly associated with malaria infection. Conclusion The study revealed the prevalence of malaria infection among the adolescents in rural Southwestern Nigeria. There may be need to pay greater attention to adolescent populations for malaria intervention and control programs.

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Review Comments to the Author Reviewer #1
The discussion needs a major review, for instance there was no basis for comparing the prevalence of this study to those whose patient selection was not similar. The result of this study cannot be compared to that of Akure or Lagos where the study populations were apparently health and of different ages.
-Outdoor transmissions or development of immunity were not assessed in this study, so they cannot be implied as stated in the discussion. Same with exposure to constant mosquito bites in participants, which was assumed.
Authors should indicate if prevalence of malaria parasitaemia in table 2 was derived from thick film or thin film? Findings from thick film and thin film were not clearly stated in the result section.
Some few grammatical errors:-First line of quality control, "is" should be changed to "was", Sides not slide, reproduced not reproduce Regarding the treatment of respondents: Better to clarify that the results were "transmitted to the managing physicians through the patients" than to just write that test results were given to respondents How was the P. falciparum specie determined in this study? Limitations-Self report of too many limitations is not good, especially when some of them are avoidable. Sample size should not be a limitation since it was scientifically derived Failure to find out the quality of LLITNs is an admission of negligence by the research team, rather than limitation. Better to keep quiet about this.
The conclusion of high malaria prevalence in this study area cannot be safely derived from febrile subjects. This gives a impression that the subjects were apparently healthy.
Overall, this is a good study that is worthy of attention if the results and discussion are well revised

Introduction
The WHO epidemiological record and others references should be updated (for example, instead of WHO 2015 report use the actual report!)

Materials and methods
The determination of the genotype was not completely described. This should be done. Results - Table 2: the parenthesis should be completed; ggg - The age and sex should also be considered since the authors have divided the population into two groups (see Table 1) Limitations: The lack of children less than 10 years old is also a possible limitation for having a reel burden of malaria in these older children and adolescent.

END
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The description of genotype determination has been modified. See page 9, line 204-205 This statement is required for submission and will appear in the published article if the submission is accepted. Please make sure it is accurate.
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Hematological changes are other factors that may contribute to the transmission of microscopic malaria infection especially in children [7,13]. These changes may be related to the individual's packed cell volume, ABO blood grouping, and hemoglobin electrophoresis pattern [7,13].
Anemia has been known to be the usual sign of the parasitic infection in endemic malaria areas with P. falciparum being an important contributor to anemia in children [7,14]. Anemia is defined as a decrease in number of red blood cells (RBCs) or less than the normal quantity of hemoglobin for an individual's age and gender. From the age of puberty, hemoglobin of less than 10.0g/dl indicates anemia [14]. Resistance to malaria is characterized by the development of an immune response acquired by the host and also depends on innate features as protective factor against infections. Such innate features include ABO blood grouping, sickle cell trait (HbAS), and sickle cell disease (HbSS) [15]. The role of ABO blood group and the genetic make-up in adolescents susceptibility to malaria have not been fully studies [7,[13][14]. Though, many studies on the association of malaria infection with ABO blood grouping and hemoglobin genotype have been reported in urban areas of Nigeria, majority of such studies were conducted in pregnant women and the under five children as the most vulnerable [7,8,13]. However, there is increasing evidence suggesting that school aged children and adolescents especially in rural settings are contributing to the number of population at risk of malaria [13,14]. Moreover, due to a decline in transmission and exposure in some areas, the peak age of clinical attacks of malaria is shifting from very young to older children and adolescents [13,15].
In order to adapt malaria control strategies to changes in transmission patterns in rural settings, there is urgent need for data on prevalence of P. falciparum infection and its associated factors among adolescent age groups in rural Nigeria. Identifying key risk factors are crucial for the effective implementation of preventive and health intervention programs. It is also essential for policy formulation specifically for low-resource settings. Therefore, this study is aimed to  [17]. In the study area, malaria transmission is perennial during the raining season (April -October) with P. falciparum being the major causative agent [17]. The health facility offers secondary and tertiary care to the people of its catchment area and its neighborhood states. The hospital has three outreach branches and was an accredited centre for postgraduate residency training in family medicine, pediatrics and other core clinical specialties. Recruitment procedure and collection of data were done by the trained resident doctors and medical officers at the family medicine, Igogo and Ado clinics, and adult emergency unit of FETHI..

Study population:
This comprised all adolescent populations who presented to the family medicine, Igogo and Ado clinics, and adult emergency unit of the hospital.
Inclusion Criteria: Adolescent patients aged 10-19 years bracket who presented with febrile illness (with an axillary temperature ≥37.5 0 C) and included those who consented (aged 18 years and above) and those who assented by adults (below 18 years of age). Recruitment procedure: The data were collected using a pretested semi-structured interviewer administered questionnaire which was developed by the researcher. To ensure construct validity, the pretesting of the questionnaires was carried out on 10 febrile adolescent patients who were selected randomly at the family medicine clinic of nearby tertiary health facility. The pretesting was to see to the applicability of the instrument and recruitment procedure. Feedback from the pretest and validity assessment led to some modifications in the questionnaires. The questionnaires were translated from English to Yoruba language for those who did not understand English with the assistance of the interpreter while back translated to English language was subsequently done to maintain response consistency. The questionnaires took between 8 to 10 minutes to complete.

Clinical parameters of the respondents:
Sample collection: Samples of blood (about 5ml) were obtained intravenously with the assistance of hospital phlebotomist. The blood samples were transferred into an ethylenediaminetetraacetic acid (EDTA) bottle to prevent blood coagulation.

Microscopy for malaria parasite:
Two blood films, one thin and one thick were made from the blood samples. The thick and thin smears were prepared on clean, dry microscope glass slides and were allowed to dry. The thin smear was fixed in methanol and both smears were stained with 2% Giemsa BDH Laboratory supplies; Poole BH 15 ITD England [21]. The slides were viewed under a microscope using oil immersion at Quality control: To ensure that the authorized standard operating procedure is followed for all the investigations, a senior scientist was recruited to examine the slide for quality control. Our methodology may be reproduce by fellow researchers if they so desire.

Treatment of the respondents:
The results of blood film examination were given to the respondents. Respondents diagnosed with malaria and anemia were treated.
Data entry and analysis: Data collected were checked, cleaned and entered into EPI Info Version 7.0 and were exported to IBM SPSS for window version 21.0 (IBM Corp., Armonk, NY,USA), respectively for analysis. Quantitative data were expressed as mean ± standard deviation. Frequencies were used to determine the prevalence of malaria infection in the respondents. Binary logistic regression was employed to assess the determinants of Plasmodium infection. Variables significant at P-value < 0.05 in the univariate logistic regression were selected for multivariate logistic regression analysis model. Odds ratios with 95% confidence intervals were calculated and P-value< 0.05 was considered to be statistically significant.

Results:
A total of 180 respondents were screened during the study period.

Discussion:
The study identified the prevalence of malaria infection and examined the socio-demographics, LLINs Usage and hematological parameters-based factors that determine the likelihood of malaria infection among adolescents aged 10-19 years in rural Southwestern Nigeria. The prevalence of 71.1% (95% CI: 68.2%-73.8%) found in this study revealed that the malaria infection was higher among the adolescent age groups. This finding was comparable to a cross sectional study conducted among school aged participants in Akure Southwestern Nigeria (71.7%) [19], and Abia Southeastern Nigeria (68.1%) [ 25]. This similarity in the prevalence might be due to the use of bed nets and gradual development of immunity, to a lesser extent, outdoor transmission [8,11]. In contrast, this study showed a higher prevalence of malaria than a cross sectional study conducted in Lagos Southwestern Nigeria ( . This could be due to the fact that while this current study was conducted during the peak of the raining season, the study in Lagos was conducted during the dry season, and other studies were conducted in Northern Nigeria. A study carried out across the six geopolitical regions of the country in 2010 concluded that the prevalence of malaria infection was higher in the Southwestern Nigeria compared to the Northern Nigeria [25]. Thus, differences in location, season variation, climatic conditions, and environmental factors might be responsible for this finding [9]. Furthermore, the prevalence of malaria in this study was lower than a cross sectional study conducted among first year student in Southeastern Nigeria (80.0%) [29], and in Southern Tanzania (78.0%) [30]. The low prevalence in this study compared to the other previous malaria study in Awka, Southeastern Nigeria might be attributed to the usage of insecticide treated nets as well as the setting. However, it is noteworthy to state that malaria prevalence recorded in this study is of public health importance and could be attributed to several factors in the study area such as climatic, vegetation and environmental factors and the increase chances of participants contact with malaria.
Furthermore, our finding revealed that P. falciparum was the only plasmodium species encountered in this study. This is comparable to cross sectional studies conducted in Ekiti [31], and Akure [19], Southwestern Nigeria, and other malaria endemic setting [14]. This finding was not surprised given the fact that P. falciparum is the dominant Plasmodium species in Southwestern Nigeria [19,31], and in Africa [32], and 99.7% estimated malaria cases of P.
falciparum have been documented from WHO African regions [1]. It is responsible for the reported high morbidity and mortality among children, especially in sub-Sahara Africa countries.
Using multivariate regression for factors that were significantly associated with malaria infection in this study, respondents who had no formal education were 3.403 times more likely to increase the odds of malaria infection as compared to those who had formal education. This was similar to cross sectional studies conducted in Ibadan Southwestern Nigeria [11], Kano Northwestern Nigeria [9], and Kenya [33] which showed that level of education significantly influences the knowledge, attitude, and practice of people in various malaria interventions, treatment, and Similarly, the respondents who resided in the rural setting were 4.821 times more likely to increase the odds of malaria infection. This was in agreement with studies conducted in Ibadan Southwestern Nigeria [11] and Kenya [8]. However, other cross sectional studies conducted in Kano Northwestern Nigeria [27], and other Africa country [34] have reported a high prevalence of malaria infection among the urban residents. The increased odds of malaria infection among the rural dwellers in this study may be due to their increased exposure to constant mosquito bites due to their poor housing and environmental factors. Other studies have attributed the increased odds of malaria infection in rural areas to lack of social mobilization concerning malaria prevention [8,33].
In this study, although, respondents reported ownership of a LLIN (71.7%), they do not consistently use it, as only 43.3% of the respondents reported to have been consistently sleeping under LLINs. This was in agreement with cross sectional studies conducted in various parts of Africa, where LLIN has been shown to be at its lowest among school children [7,11,25].
Prevention communication strategies geared towards transmission of ownership into usage are recommended. The use of LLINs in this study was found to be significantly associated with reduction of malaria infection as the results showed that respondents who failed to sleep under LLINs were 1.950 times more likely to have malaria infection as compared to the respondents who did. This finding was consistent with the reports of studies conducted in central Nigeria [7], Southwestern Nigeria [11], and western Kenya [35]. Appropriate utilization of LLINs is one of the major cost effective interventions adopted for the prevention of malaria transmission. This finding further reinforces the usefulness of LLINs and calls for its continuous awareness campaign to improve its usage in rural settings.
The study showed that respondents who were of hemoglobin genotype AA and AS were associated with increased odds of malaria infections. This was consistent with the reports of cross sectional studies conducted in Sokoto North Western Nigeria [14 ] and Osun, Southwestern Nigeria [36] which found hemoglobin AA and AS to be a predictors of malaria infection. However, reports by several other studies on the association between hemoglobin genotype and malaria infection have been inconsistent [13][14][15] [7], study by Amala et al in River State Nigeria found HbAS as most protective against severe malaria [15]. These variations in the reports by these several studies suggest that other factors like geographical, environmental, and climatic may be responsible for the transmission of malaria infection irrespective of the hemoglobin genotype [13,15,33].
This study also showed that rhesus positive respondents is the most dominant with 86.7% and was found to be 1.815 times more likely to increase the odds of malaria infection as compared to rhesus negative respondents. This finding was comparable with the reports of cross sectional study conducted in Okada Nigeria [38]. Although, there was no obvious reason for this outcome, the proportion of respondents with rhesus negative in this study (13.3%) should not be discarded, given its implications in abortion and the hemolytic disease of the new born [37].
In this study, anemia was found to be significantly associated with malaria infection. This finding was consistent with the reports of previous studies conducted among school aged populations in Abia State [25], and Osun State Nigeria [36]. However, study by Umaru and colleague in Kaduna State Nigeria found no significant association between anemia and malaria infection [28]. The mechanism through which malaria infection causes anemia is multifactorials. In rural settings like the study area, as micronutrients deficiency is common in many malaria endemic settings, it is possible that these respondents may have been anemic initially, and malaria infection further added to the burden of anemia [28]. Our study showed that the increased prevalence of malaria infection among these adolescents, demonstrate that, a reduction in packed cell volume is associated with risk of malaria infection [28,36]. Physiologically, school aged children are susceptible to malaria infection due to their loss of acquired immunity, and thus increased likelihood of being anemic [28,32].

Limitations:
This study was based on cross sectional design and thus, had limited opportunities to measure any causal association between malaria infection and other factors. The sample size was small, therefore, findings may not represent the general population. The age and quality of the LLINs were not considered and information on its use was self-reported. Bed nets may have been torn or of poor conditions and therefore, failed to provide adequate protection, as has been previously reported in Kenya. 35 Hemoglobin level was only assessed at baseline, measurement of hemoglobin level for each suspected case could have provided a better assessment of the association between anemia and malaria in the study area. 35 Despite these limitations, the study generates distinctive information regarding the burden of, and associated risk factors for malaria infection among the adolescents, which could be helpful for formulating further steps to implement interventions in rural Southwestern Nigeria.

Conclusion:
The study showed a higher prevalence of malaria infection among the adolescent populations in rural Southwestern Nigeria. Lack of formal education, being a rural residence, not sleeping under LLINs, blood hemoglobin genotype AA and AS, rhesus positive individuals, and having severe anaemia were significantly associated with the risk of malaria infection. The study demonstrated the need to pay greater attention to adolescent populations in rural settings for malaria interventions and control programs. The results may assist the stakeholders in decision making to formulate further steps towards improved malaria prevention and control.

Acknowledgements:
The authors would like to appreciate the participants, and also nurses, resident doctors and medical officers at the family medicine, outreach centers, and adult emergency medicine departments and the management of FETHI where the study was conducted.   Malaria remains a global disease burden, and is a major public health concern in many countries 54 including Nigeria [1]. The disease is transmitted in humans from one person to another through 55 the bites of infected female mosquitoes of the Anopheles [2,3]. There are five species of parasites 56 belonging to the genus Plasmodium, that transmit malaria, of which P. falciparum being the 57 most prevalent [2,3]. Globally, there were 247 million cases of malaria and 619,000 deaths in 58 2021 [4]. However, approximately 80% of all deaths due to malaria were concentrated in just 15 59 countries mainly in the Africa region [2]. Despite frantic efforts and interventions targeted at its 60 elimination, 48% of the world population remain exposed to the risk of malaria, a figure   61 substantially higher than the 40% widely cited [4]. In Africa, malaria is the leading cause of 62 hospital admissions and out-patient consultations [5,6]. 63 The prevalence of malaria infection among the adolescent patients varies from place to place, 64 even within the same country, and may be due to differences in socio-demographic, 65 environmental and climatic factors [7,8]. In Nigeria, malaria prevalence of 66.7% [9], 64.0% 66 [10], and 58.0% [11] have been reported by previous studies. Socio-demographic factors such as 67 age, gender, education, occupation and income, which may directly affect human exposure and 68 treatment, and climatic factors such as temperature, humidity, and rainfall which may support 69 rapid growth and development of mosquito vectors have been well reported in urban and peri-70 urban centers [8,11]. In Africa, malaria transmission is comparatively higher among the rural 71 settings than the urban areas, which may be due to the higher vector density, poor housing status, 72 and poor drainage systems in rural settings [8,12].

73
Hematological changes are other factors that may contribute to the transmission of microscopic 74 malaria infection especially in children [7,13]. These changes may be related to the individual's 75 4 packed cell volume, ABO blood grouping, and hemoglobin electrophoresis pattern [7,13]. 76 Anemia has been known to be the usual sign of the parasitic infection in endemic malaria areas 77 with P. falciparum being an important contributor to anemia in children [7,14]. Anemia is 78 defined as a decrease in number of red blood cells (RBCs) or less than the normal quantity of 79 hemoglobin for an individual's age and gender. From the age of puberty, hemoglobin of less than 80 10.0g/dl indicates anemia [14]. Resistance to malaria is characterized by the development of an 81 immune response acquired by the host and also depends on innate features as protective factor 82 against infections. Such innate features include ABO blood grouping, sickle cell trait (HbAS), 83 and sickle cell disease (HbSS) [15]. The role of ABO blood group and the genetic make-up in 84 adolescents susceptibility to malaria have not been fully studies [7,[13][14]. Though, many studies 85 on malaria infection with ABO blood grouping and hemoglobin genotype have been reported in 86 urban areas of Nigeria, majority of such studies were conducted in pregnant women and the 87 under five children [7,8,13]. However, there is increasing evidence suggesting that school aged 88 children and adolescents are contributing to the number of population at risk of malaria [13,14]. 89 Moreover, due to a decline in transmission and exposure in some areas, the peak age of clinical 90 attacks of malaria is shifting from very young to older children and adolescents [13,15].

91
In order to adapt malaria control strategies to changes in transmission patterns in rural settings,  working population and retirees in the formal sector [17]. In the study area, malaria transmission 108 is perennial during the raining season (April -October) with P. falciparum being the major 109 causative agent [17]. The health facility offers secondary and tertiary care to the people of its   illness (with an axillary temperature ≥37.5 0 C) and included those who consented (aged 18 years 119 and above) and those who assented by adults (below 18 years of age). Exclusion Criteria: Patients who were too ill that required immediate attention or those with 121 mental illness. Also, those on treatment for malaria or have just completed anti malaria within 122 two weeks prior to the conduct of this study.

123
Sample size determination: This was determined using Araoye formular [18]. 124 n = Z 2 P(1-P) and nf = 1+ with a prevalence (P) of 84.2% [19] in a previous study on  privacy were ensured throughout the study. The study was at no cost to the respondents. All  8000 per ul of blood [21]. The degree of parasite density was graded as mild, moderate, 194 and severe when the counts were <1000 parasites/ul of blood, 1000-9999/ul of blood, and 195 ≥ 10,000/ul of blood, respectively, following the method described elsewhere [9].

214
Quality control: To ensure that the authorized standard operating procedure was followed for 215 all the investigations, a senior scientist was recruited to examine the slides for quality control.

216
Our methodology may be reproduced by fellow researchers if they so desire. USA), respectively for analysis. Quantitative data were expressed as mean ± standard deviation.

223
Frequencies were used to determine the prevalence of malaria infection in the respondents.

224
Binary logistic regression was employed to assess the determinants of Plasmodium infection.   rural areas to lack of social mobilization concerning malaria prevention [8,33]. 318 In this study, although, respondents reported ownership of a LLIN (71.7%), they do not 319 consistently use it, as only 43.3% of the respondents reported to have been consistently sleeping 320 under LLINs. This was in agreement with cross sectional studies conducted in various parts of 321 Africa, where LLIN has been shown to be at its lowest among school children [7,11,25]. likely to have malaria infection as compared to the respondents who did. This finding was 327 consistent with the reports of studies conducted in central Nigeria [7], Southwestern Nigeria 328 [11], and western Kenya [35]. Appropriate utilization of LLINs is one of the major cost effective 329 interventions adopted for the prevention of malaria transmission in endemic settings [28,31]. 330 This finding further reinforces the usefulness of LLINs and calls for its continuous awareness 331 campaign to improve its usage in rural settings [28]. 332 The study showed that respondents who were of hemoglobin genotype AA and AS were 333 associated with increased odds of malaria infections. This was consistent with the reports of 334 cross sectional studies conducted in Sokoto North Western Nigeria [14 ] and Osun, 335 Southwestern Nigeria [36] which found hemoglobin AA and AS to be a predictors of malaria 336 infection. However, reports by several other studies on the association between hemoglobin 337 genotype and malaria infection have been inconsistent [13][14][15] severe malaria [15]. These variations in the reports by these several studies suggest that other 342 factors like geographical, environmental, and climatic may be responsible for the transmission of 343 malaria infection irrespective of the hemoglobin genotype [13,15,33].

344
This study also showed that rhesus positive respondents is the most dominant with 86.7% and  In this study, anemia was found to be significantly associated with malaria infection. This                   Malaria remains a global disease burden, and is a major public health concern in many countries 54 including Nigeria [1]. The disease is transmitted in humans from one person to another through 55 the bites of infected female mosquitoes of the Anopheles [2,3]. There are five species of parasites 56 belonging to the genus Plasmodium, that transmit malaria, of which P. falciparum being the 57 most prevalent [2,3]. Globally, there were 247 million cases of malaria and 619,000 deaths in 58 2021 [4]. However, approximately 80% of all deaths due to malaria were concentrated in just 15 59 countries mainly in the Africa region [2]. Despite frantic efforts and interventions targeted at its 60 elimination, 48% of the world population remain exposed to the risk of malaria, a figure   61 substantially higher than the 40% widely cited [4]. In Africa, malaria is the leading cause of 62 hospital admissions and out-patient consultations [5,6].

63
The prevalence of malaria infection among the adolescent patients varies from place to place, 64 even within the same country, and may be due to differences in socio-demographic, 65 environmental and climatic factors [7,8]. In Nigeria, malaria prevalence of 66.7% [9], 64.0% 66 [10], and 58.0% [11] have been reported by previous studies. Socio-demographic factors such as 67 age, gender, education, occupation and income, which may directly affect human exposure and 68 treatment, and climatic factors such as temperature, humidity, and rainfall which may support 69 rapid growth and development of mosquito vectors have been well reported in urban and peri-70 urban centers [8,11]. In Africa, malaria transmission is comparatively higher among the rural 71 settings than the urban areas, which may be due to the higher vector density, poor housing status, 72 and poor drainage systems in rural settings [8,12].

73
Hematological changes are other factors that may contribute to the transmission of microscopic 74 malaria infection especially in children [7,13]. These changes may be related to the individual's 75 4 packed cell volume, ABO blood grouping, and hemoglobin electrophoresis pattern [7,13]. 76 Anemia has been known to be the usual sign of the parasitic infection in endemic malaria areas 77 with P. falciparum being an important contributor to anemia in children [7,14]. Anemia is 78 defined as a decrease in number of red blood cells (RBCs) or less than the normal quantity of 79 hemoglobin for an individual's age and gender. From the age of puberty, hemoglobin of less than 80 10.0g/dl indicates anemia [14]. Resistance to malaria is characterized by the development of an 81 immune response acquired by the host and also depends on innate features as protective factor 82 against infections. Such innate features include ABO blood grouping, sickle cell trait (HbAS), 83 and sickle cell disease (HbSS) [15]. The role of ABO blood group and the genetic make-up in 84 adolescents susceptibility to malaria have not been fully studies [7,[13][14]. Though, many studies 85 on malaria infection with ABO blood grouping and hemoglobin genotype have been reported in 86 urban areas of Nigeria, majority of such studies were conducted in pregnant women and the 87 under five children [7,8,13]. However, there is increasing evidence suggesting that school aged 88 children and adolescents are contributing to the number of population at risk of malaria [13,14]. 89 Moreover, due to a decline in transmission and exposure in some areas, the peak age of clinical 90 attacks of malaria is shifting from very young to older children and adolescents [13,15].

91
In order to adapt malaria control strategies to changes in transmission patterns in rural settings, working population and retirees in the formal sector [17]. In the study area, malaria transmission 108 is perennial during the raining season (April -October) with P. falciparum being the major 109 causative agent [17]. The health facility offers secondary and tertiary care to the people of its  illness (with an axillary temperature ≥37.5 0 C) and included those who consented (aged 18 years 119 and above) and those who assented by adults (below 18 years of age). Exclusion Criteria: Patients who were too ill that required immediate attention or those with 121 mental illness. Also, those on treatment for malaria or have just completed anti malaria within 122 two weeks prior to the conduct of this study.

123
Sample size determination: This was determined using Araoye formular [18]. 124 n = Z 2 P(1-P) and nf = 1+ with a prevalence (P) of 84.2% [19] in a previous study on  privacy were ensured throughout the study. The study was at no cost to the respondents. All 8000 per ul of blood [21]. The degree of parasite density was graded as mild, moderate, 194 and severe when the counts were <1000 parasites/ul of blood, 1000-9999/ul of blood, and 195 ≥ 10,000/ul of blood, respectively, following the method described elsewhere [9].

214
Quality control: To ensure that the authorized standard operating procedure was followed for 215 all the investigations, a senior scientist was recruited to examine the slides for quality control.

216
Our methodology may be reproduced by fellow researchers if they so desire. USA), respectively for analysis. Quantitative data were expressed as mean ± standard deviation.

223
Frequencies were used to determine the prevalence of malaria infection in the respondents.

224
Binary logistic regression was employed to assess the determinants of Plasmodium infection.  the respondents who had severe anemia, (Table 3). 265 13 It is responsible for the reported high morbidity and mortality among children, especially in sub-302 Sahara Africa countries. Using multivariate regression for factors that were significantly 303 associated with malaria infection in this study, respondents who had no formal education were 304 3.403 times more likely to increase the odds of malaria infection as compared to those who had 305 formal education. This was similar to cross sectional studies conducted in Ibadan Southwestern 306 Nigeria [11], Kano Northwestern Nigeria [9], and Kenya [33] which showed that level of 307 education significantly influences the knowledge, attitude, and practice of people in various 308 malaria interventions, treatment, and control [9,11,31,33]. 309 Similarly, the respondents who resided in the rural setting were 4.821 times more likely to 310 increase the odds of malaria infection. This was in agreement with studies conducted in Ibadan 311 Southwestern Nigeria [11] and Kenya [8]. However, other cross sectional studies conducted in infections in this study. Other studies have attributed the increased odds of malaria infection in 317 rural areas to lack of social mobilization concerning malaria prevention [8,33]. 318 In this study, although, respondents reported ownership of a LLIN (71.7%), they do not 319 consistently use it, as only 43.3% of the respondents reported to have been consistently sleeping 320 under LLINs. This was in agreement with cross sectional studies conducted in various parts of 321 Africa, where LLIN has been shown to be at its lowest among school children [7,11,25]. LLINs in this study was found to be significantly associated with reduction of malaria infection 325 as the results showed that respondents who failed to sleep under LLINs were 1.950 times more 326 likely to have malaria infection as compared to the respondents who did. This finding was 327 consistent with the reports of studies conducted in central Nigeria [7], Southwestern Nigeria 328 [11], and western Kenya [35]. Appropriate utilization of LLINs is one of the major cost effective 329 interventions adopted for the prevention of malaria transmission in endemic settings [28,31]. 330 This finding further reinforces the usefulness of LLINs and calls for its continuous awareness 331 campaign to improve its usage in rural settings [28]. 332 The study showed that respondents who were of hemoglobin genotype AA and AS were 333 associated with increased odds of malaria infections. This was consistent with the reports of 334 cross sectional studies conducted in Sokoto North Western Nigeria [14 ] and Osun, 335 Southwestern Nigeria [36] which found hemoglobin AA and AS to be a predictors of malaria 336 infection. However, reports by several other studies on the association between hemoglobin 337 genotype and malaria infection have been inconsistent [13][14][15]. Study by Suchdev et al in Kenya 338 had found no significant association between malaria infection and hemoglobin genotype AA,

Reviewer's comments Authors' Response
Editor's comment: In addition to the comments raised by the reviewers, the authors will need to re-work the data analysis in Table 3, particularly the percentages and carefully go through the entire manuscript to correct grammatical errors as well as italicize all scientific names.
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---The data has been reviewed and errors have been corrected. Check table 3 page 13. All scientific names have been italicized.
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Introduction
The WHO epidemiological record and others references should be updated (for example, instead of WHO 2015 report use the actual report!)

Materials and methods
The determination of the genotype was not completely described. This should be done. Results - The age and sex should also be considered since the authors have divided the population into two groups (see Table 1) Limitations: The lack of children less than 10 years old is also a possible limitation for having a reel burden of malaria in these older children and adolescent.

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The affected sentences in the introduction have been updated including the references. See page 3, line 58-63 and references 2-6 under references.
The description of genotype determination has been modified. See page 9, line 204-205